A normal heart rate for healthy adults, during rest can range from 60 to 100 beats per minute (bpm) but can drop to 40 bpm during sleep and go as high as 240 bpm during vigorous exercise. One commonly used maximum heart rate formula is: Max HR=220 minus Age. Clearly, for infants and premature babies, their heart rates are quite high. Our previous patent application: “Systems And Methods For Non-Contact Heart Rate Sensing”, U.S. patent application Ser. No. 13/247,575, by Mestha et al., disclosed a method for analyzing a video to determine a subject's heart rate. For large patient populations and various living conditions, this heart rate algorithm may have to step through 40 bpm to an ultimate maximum of 240 bpm in at least one beat per minute intervals. While sweeping through 1 bpm steps, there is a single frequency (very close to the true pulse) for which the error is very close to zero. FIG. 1 shows an error plot with one infant video between an input heart rate to an extracted heart rate using the previously disclosed method for a limited range of 120 to 240 bpm. Because one needs to step through as many as 180 intervals per batch to achieve a resolution of 1 bpm, this can be computationally intensive when such operations have to be performed repeatedly for every new batch of new data during continuous monitoring. What is desirable is a method for computing a subject's cardiac pulse across a large range, i.e., from about 40 bpm to 240 bpm, in at least one beat per minute intervals, in a computationally efficient manner for continuous monitoring or when a large number of sequential segments have to be processed.
Accordingly, what is needed in this art is a computationally efficient system and method for estimating a subject's cardiac pulse rate from multi-channel source video data that can be used in a continuous monitoring mode with a high degree of measurement accuracy.